Article ID Journal Published Year Pages File Type
7358273 Journal of Econometrics 2017 16 Pages PDF
Abstract
This paper constructs an estimator for the number of common factors in a setting where both the sampling frequency and the number of variables increase. Empirically, we document that the covariance matrix of a large portfolio of US equities is well represented by a low rank common structure with sparse residual matrix. When employed for out-of-sample portfolio allocation, the proposed estimator largely outperforms the sample covariance estimator.
Related Topics
Physical Sciences and Engineering Mathematics Statistics and Probability
Authors
, ,